Course detail

Statistics

FP-STA1Acad. year: 2023/2024

Students will acquire basic knowledge of probability theory, random variables, random vectors, system reliability, index analysis, decision making under risk and uncertainty and descriptive statistics.

Language of instruction

Czech

Number of ECTS credits

6

Mode of study

Not applicable.

Guarantor

Ing. Karel Doubravský, Ph.D.

Department

Institute of Informatics (ÚI)

Entry knowledge

Not applicable.

Rules for evaluation and completion of the course

The course-unit credit is awarded on the following conditions (max. 40 points):
- elaboration of control tests.
-active participation in seminars 80% (any higher absence will be replaced by solving and submitting the additional examples).


The exam (max. 60 points)
- has a written form.
In the first part of the exam student solves 4 examples within 80 minutes. In the second part of the exam student works out answers to 3 theoretical questions within 15 minutes.

The mark, which corresponds to the total sum of points achieved (max. 100 points), consists of:
- of points achieved in control tests,
- points achieved by solving examples,
- points achieved by answering theoretical questions.

The grades and corresponding points:
A (100-90), B (89-83), C (82-76), D (75-69), E (68-60), F (59-0).

Attendance at lectures is not mandatory but is recommended. Attendance at exercises is required and checked by the tutor. An excused absence of a student from seminars can be compensated for by submitting solution of alternate exercises.

Aims

Learning outcomes of the course unit is to acquaint students with the basics of probability theory, random variables, index analysis, decision-making under risk and uncertainty and descriptive statistics so that they are able to apply this knowledge appropriately in management, informatics and economic problems.
Students will acquire basic knowledge of probability theory, random variables, random vectors, system reliability, index analysis, decision making under risk and uncertainty, descriptive statistics.
At the end of the course students will be able to use these methods in related subjects.

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

KROPÁČ, J. STATISTIKA A. 5. vyd. Brno: Fakulta podnikatelská, VUT v Brně, 2013. 140 s. ISBN 978-80-7204-835-9.
KROPÁČ, J. Statistika. 2. vyd. Brno: Akademické nakladatelství CERM, 2012. ISBN 978-80-7204-788-8.

Recommended reading

BUDÍKOVÁ, M.; LERCH, T. a MIKOLÁŠ, Š. Základní statistické metody. 1. vyd. Brno: Masarykova univerzita v Brně, 2005. ISBN 80-210-3886-1.
HINDLS, R. et al. Analýza dat v manažerském rozhodování. Praha : Grada Publishing, 1999. ISBN 80-7169-255-7.
KROPÁČ, J. Statistika B. 2. vyd. Brno: Fakulta podnikatelská, 2009. ISBN 978-80-214-3295-6.
SWOBODA, H. Moderní statistika. Praha : Svoboda, 1977.

Elearning

eLearning: currently opened course

Classification of course in study plans

  • Programme BAK-MIn Bachelor's 2 year of study, winter semester, compulsory

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

Mgr. Milan Křápek, Ph.D.

Syllabus

1. Classical probability
2. Conditional probability
3. Random variables
4. Discrete random variables
5. Continuous random variables
6. Theorem of Moivre-Laplace
7. Reliability of systems
8. Random vectors
9. Individual indices
10. Compound indexes
11. Decision making under risk
12. Decision trees
13. One-dimensional data sets of quantitative characters

Exercise

26 hod., compulsory

Teacher / Lecturer

Mgr. Milan Křápek, Ph.D.

Syllabus

The topics of exercises correspond to the topics of lectures.

Elearning

eLearning: currently opened course